man.load_from_hdf(h5_filename)
dp = DoublePlotter()
sp = StimulPlotter()
for spine_num in stimulated_spines:
name = None
fig_filename = None
name = 'ele_bio_' + condition + "_" + spine_num + '.png'
fig_filename = os.path.join(dir, name)
if not os.path.exists(fig_filename):
biogroup = 'timeSeries_' + spine_num
fig = plt.figure()
ax1, ax2 = dp.plot_double_axes(man, spine_num, 'v',
'AMPAR_P', bio_group=biogroup)
ax1.set_ylim(-90, 0)
ax2.set_ylim(10, 150) # make space for the legend.
sp.plot_input(spine_num, man, ax=ax1)
for ext in ['.png', '.pdf']:
name = 'ele_bio_' + condition + "_" + spine_num + ext
fig_filename = os.path.join(dir, name)
plt.savefig(fig_filename)
print "Saved file %s" %fig_filename
else:
print "File %s exist. Skipping" %fig_filename
del man
else:
print "Skipping dir %s" %dir
for spine_num in stimulated_spines:
name = None
fig_filename = None
name = prefix + condition + "_" + spine_num + '.png'
fig_filename = os.path.join(dir, name)
if not os.path.exists(fig_filename):
biogroup = 'timeSeries_' + spine_num
fig = plt.figure()
sec_name = "%s_head" %spine_num
t = man.groups['t']
cali = man.get_vector(sec_name, 'cali')
cai = man.get_vector(sec_name, 'cai')
ca = cai+cali
label ="%s_ca" %spine_num
plt.plot(t, ca, 'g-', label=label)
plt.xlabel('Time [ms]')
plt.ylabel('Concentration [mM]')
sp.plot_input(spine_num, man, height_in_the_graph=0.0005)
#plt.ylim(0, 0.010)
for ext in ['.png', '.pdf']:
name = prefix + condition + "_" + spine_num + ext
fig_filename = os.path.join(dir, name)
plt.savefig(fig_filename)
print "Saved file %s" %fig_filename
else:
print "File %s exist. Skipping" %fig_filename
del man
else:
print "Skipping dir %s" %dir
